Location-Guided Visual Code Scanning Using Geolocation Pre-Filtering
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Solution Overview
Problem
Current visual codes, such as QR codes, require users to scan them at close distances for reliable decoding, limiting their deployability and usage due to issues with low resolution and bit loss when scanned from far distances.
Innovation Solution
The implementation of a far code scanner system that uses geographical location information and crowdsourced data to generate a narrowed list of possible visual codes, allowing for location-guided visual code scanning from long distances by aligning and decoding captured visual codes using neural networks and computer vision algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If visual codes are scanned from far distances, then the scanning range is extended, but the decoding reliability deteriorates due to low resolution and bit loss
Solution Approach 1:
The system performs preliminary actions by using geographical location information to predict and narrow down the list of possible visual codes before actual decoding occurs. This pre-filtering based on location data prepares a constrained set of candidate codes, making the subsequent decoding process more reliable even when the captured image quality is poor due to distance.
Solution Approach 2:
The patent introduces an intermediary mechanism - a server system that acts as a mediator between the captured visual code and the final decoding result. The server receives the captured code along with location information, narrows down possible matches using location data, and performs the actual decoding. This intermediary process bridges the gap between poor-quality distant scans and reliable decoding.
2Adaptability or versatility
If visual codes are scanned from far distances, then the deployability is improved, but the image quality deteriorates due to low resolution
Solution Approach 1:
The system uses location information to pre-narrow the list of possible visual codes before decoding attempts. This preliminary filtering based on geographical context allows the system to handle lower quality images from distant scans by focusing computational resources on a constrained set of likely candidates, thereby improving deployability without requiring high image quality.
Solution Approach 2:
The system implements a feedback mechanism where location information is continuously used to refine and narrow the list of candidate visual codes. The server receives location data, compares it with known visual code locations, and provides feedback in the form of a narrowed candidate list, which improves the system's ability to handle varied scanning conditions and distances.
Data Source
AI summary
A method of implementing location-guided visual code scanning from long distances starts with a processor receiving from client device a media content item and a location of the client device. Processor detects a portion of the media content item including image of captured visual code. Processor aligns image of captured visual code in the portion of the media content item to generate rectified image of captured visual code. Processor selects, based on location of the client device, subset of visual codes of the visual codes in database that stores visual codes and visual code location estimates associated with the plurality of visual codes. Processor detects matching visual code from the subset of visual codes using the rectified image of the captured visual code and causes a selectable item associated with the matching visual code to be displayed by the client device. Other embodiments are described herein.